Since verification applications like person re-identification (re-id) [1]} usually train metric learning models along with classification, recent work [2]} leverages the classification activation map to improve the performance, but the activation map of metric learning is still not well explored. For two given images, a variant of Grad-CAM has been used for visualization of image retrieval [3]} by computing the gradient from the cosine similarity of the embedding features to the last convolutional layers of both images. However, Grad-CAM only provides the overall highlighted regions of two input images, the relationship between each activated region of two images is yet to be uncovered. Since the similarity is calculated from two images and possibly based on several similar patterns between them, the relationship between these patterns is critical for understanding the model.
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